CV Prof. Stephan Ripke 327 KB

Total Page:16

File Type:pdf, Size:1020Kb

CV Prof. Stephan Ripke 327 KB Stephan Ripke, M.D., Ph. D. +1 857 399 5833 (US) +49 160 2409402 (Germany) [email protected] [email protected] SUMMARY . Professor for Statistical Genetics . Ph.D. with over 10 years research experience in statistical genetics . First author of multiple seminal publications in Nature and Nature Genetics . Leader of the statistical analysis group of the Psychiatric Genomics Consortium (PGC) for over 6 years . Winner of multiple awards and grants in the medical research field . Medical Doctor with 3 years of clinical training . Strong computational and statistical skills combined with extensive experience providing service analyses EXPERIENCE Broad Institute, Stanley Centre / Massachusetts General Hospital, Harvard, Cambridge, MA 10/2008 – present . Research Scientist with Mark Daly at Analytic and Translational Genetics Unit . Group Leader Statistical Analysis Group of the Psychiatric Genomics Consortium (PGC) - Applying common variant analysis, including quality control, imputation, principal component analysis, meta- and secondary analyses, as part of the PGC and also with various genetic research groups around the world. Including many larger consortiums such as the Inflammatory Bowel Disease Consortium, ENIGMA and IMAGEN - Developing a novel analysis pipeline in Perl, Python, R, C++ on the computer cluster LISA (Netherlands) and Broad Institute (Cambridge, MA) - Delivering presentations at international conferences (such as World Congress of Psychiatric Genetics, American Society of Human Genetics Meeting) and regional labs on a regular basis - Closely collaborating with leading experts in the field (Mark Daly, Shaun Purcell, Benjamin Neale, Paul deBakker, David Altshuler, Eric Lander, Mick O’Donovan, Patrick Sullivan) - Authored 100+ publications (15+ as first/last author) in the field of statistical genetics (see attached publication record) - Received multiple awards in the field of human genetics such as Theodor Reich Young Investigator Award and Sidney R. Baer, Jr., Prize (see “Awards” page 2) Charité, Department of Psychiatry, Berlin, Germany 07/2014 – present . Professor / PI Laboratory for Statistical Genetics - Leading an independently funded large-scale recruitment and research project. Currently recruiting 2000 individuals for common variant analyses - Leader of the GWAS Research Unit (“GResU”) at Berlin Institute of Health - Teaching and advising PhD students and postdoctoral fellows RESEARCH SKILLS . Experienced programmer in C/C++, awk/sed, perl, python, R, shell scripts, cluster computing (qsub, bsub, SLURM) . Genetic association analysis of large scale data with extensive experience in: - association analysis: case/control, trio, qualitative and quantitative phenotypes - data quality control, imputation of missing genetic information (HM2, HM3, 1000Genomes) - population stratification analysis (principal component analysis) - annotation (UCSC), genetic structure (LD), pathway analyses - handling, storing, extracting and combining various data formats (incl. VCF, CEL Files) - experienced user of PLINK, EIGENSTRAT, BEAGLE, METAL, MACH, IMPUTE_V2, HAPLOVIEW, SHAPEIT, EAGLE, BVFTOOLS, WG-PERMER, FINE - MAP, SUSIE and other genetic analysis tools - parametric and nonparametric linkage analysis 1 Stephan Ripke, M.D., Ph. D. +1 857 399 5833 (US) +49 160 2409402 (Germany) [email protected] [email protected] - Next Generation sequencing analysis EDUCATION 2014 Ph.D. in Statistical Genetics (Common variant analysis and psychiatric disease) Utrecht, Netherlands 2002 Doctor of Medicine (M.D.) in Statistical Genetics (linkage analysis), Hamburg, Germany 1994 – 2001 Medical Schools of the Universities of Heidelberg and Hamburg, Germany AWARDS . Heisenberg Professorship, Deutsche Forschungs Gesellschaft (DFG) 2017 . 2015 NARSAD YOUNG Investigator Grant 2015 . Paper of the Year, International Society of Psychiatric Genetics. WCPG, Toronto 2015 . The Sidney R. Baer, Jr., Prize of the Brain & Behavior Research Foundation 2014 https://bbrfoundation.org/2014-outstanding-achievement-prizewinner . Theodor Reich Young Investigator Award of the International Society of Psychiatric Genetics. 2013 http://2013.ispg.net/wp-content/uploads/2013/09/WCPGProgramBook2013.pdf (page 15) . Oral Presentation Award, WCPG, Hamburg 2012 PUBLICATIONS 173 publications with impact factor of 2564 (17/364 as first/last author), H index 85, five most important publications: . Ripke S, Schizophrenia Working Group of the Psychiatric Genomics Consortium, et al., "Biological insights from 108 schizophrenia-associated genetic loci." (2014). Nature 511(7510):421-7. (IF: 42.4) . Smoller JW*, Ripke S*, Cross-Disorder Group of the Psychiatric Genomics Consortium, et al., "Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis." (2013). Lancet 381(9875):1371- 9. (IF: 39.2) . Jostins L*, Ripke S*, et al., "Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease." (2012). Nature 491(7422):119-24. (IF: 38.6) . Ripke S*, Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium*, et al., "Genome-wide association study identifies five new schizophrenia loci." (2011). Nat Genet 43(10):969-76. (IF: 35.5) . Ripke S*, O Dushlaine C*, et al., "Genome-wide association analysis identifies 13 new risk loci for schizophrenia." (2013). Nat Genet 45(10):1150-9. (IF: 29.6) * contributed equally. For a complete list including 100+ oral presentations please see: https://scholar.google.com/citations?user=trMrAoUAAAAJ GRANTS Sum of listed third party funds: $1.533.000 . Heisenberg Professorship, DFG, 2018 - 2023 $583,000 . NARSAD, BBRF Young Investigator Grant, 2016-2018 $70.000 . Sydney Bear Prize Award, Gift $20.000 . Stanley Center Grant, 2016-2017 $183.000 . Stanley Center Grant 2017-2018 $110.000 . Stanley Center Grant 2019-2020 $150.000 . NIMH, U01, PGC3, 2017-2022 $417.000 2 .
Recommended publications
  • The Path to New Therapies for Schizophrenia and Bipolar Illness
    THE JOURNAL • PERSPECTIVE • www.fasebj.org The Path to New Therapies for Schizophrenia and Bipolar Illness Edward M. Scolnick1 Stanley Center for Psychiatric Research, Broad Institute, Cambridge, Massachusetts, USA ABSTRACT: Schizophrenia and bipolar illness are two of the most serious forms of mental illness. Until relatively recently, almost nothing was known about the molecular pathogenesis of either illness. The single largest risk factor that predisposes people to schizophrenia or bipolar illness is genetic risk. Heritability is high, and the incidence is significantly higher in identical twins than in nonidentical twins. Despite decades of work aimed at identifying the genes involved in these two illnesses, virtually no progress had been made until the past decade. With the knowledge and technologies that have been gained from the Human Genome Project, it has been possible to begin to understand the underlying genetics and to use the new information to begin the effort to discover new and better medicines to treat these illnesses. This article will describe the past decade of work toward this goal and articulate both the promise that now exists and what is still needed to bring dramatic and tangible change to patients.—Scolnick, E. M. The path to new therapies for schizophrenia and bipolar illness. FASEB J. 31, 1254–1259 (2017). www.fasebj.org KEY WORDS: genetics • pharmacology • progress In the fall of 2004, I became an associate member of the bipolar illness for many years. Virtually no reproducible Broad Institute, founded on the principle of collaboration results had been achieved. The Broad Institute had a su- among scientists at the Massachusetts Institute of Tech- perb group of scientific experts in human genetics, a field nology, Harvard, and Harvard-affiliated hospitals.
    [Show full text]
  • Aarhus University Honorary Doctorate Seminar Friday 13 September 2019 at 10.00 – 11.15
    Department of Biomedicine Center for Genomics Personalized Medicine and Personalized Medicine Aarhus University Honorary Doctorate Seminar Friday 13 September 2019 at 10.00 – 11.15 Professor Mark Daly, Institute for Molecular Medicine Finland. Analytic and Translational Genetics Unit, USA. Broad Institute of Harvard and MIT, USA. Talk: Global partnerships: From Psychiatric Genetics to FinnGen and opportunities in discovery, prevention and personalized medicine. Venue: Eduard Biermann Auditory, The Lakeside Theatres, Aarhus University, Bartholins Allé 3, 8000 Aarhus C. Programme 10.00 – 10.05 Welcome by Anders Børglum 10.05 – 10.50 AU Honorary Doctorate lecture by Mark Daly 10.50 – 11.15 Open discussion Biosketch: Mark Daly, PhD, was appointed Director of the Institute for Molecular Medicine Finland (FIMM) in February 2018. He retains also his affiliations in Boston at the Harvard Medical School, Massachusetts General Hospital and as an institute member of the Broad Institute and co-director of the Program in Medical and Population Genetics. Daly received his B.S. in physics from the Massachusetts Institute of Technology and his Ph.D. in human genetics from Leiden University, Netherlands. He received the Curt Stern Award from the American Society of Human Genetics in 2014 and is a member of the National Academy of Medicine. Department of Biomedicine Center for Genomics Personalized Medicine and Personalized Medicine His research primarily focuses on the development and application of statistical methods for the discovery and interpretation of genetic variation responsible for complex human disease. In addition to foundational work in human genetics methodology, his lab has made major contributions to gene discovery in inflammatory bowel disease, autism and schizophrenia - primarily through catalyzing global collaborative research efforts which he continues to help lead.
    [Show full text]
  • Implementing Physician Education Programs
    Informatic Imperatives for Sequencing in Large-Scale Studies Daniel MacArthur Analytic and Translational Genetics Unit, Massachusetts General Hospital Broad Institute of Harvard and MIT Harvard Medical School 1000 Genomes Project Consortium Acknowledgments • Shane McCarthy (Sanger) • Mark DePristo, Ryan Poplin and Khalid Shakir (Broad) • Mark Daly and David Altshuler (MGH/Broad) • 1000 Genomes Analysis Group A plausible near-future scenario • we have exome sequence and complex phenotype data available for 100,000 individuals from multiple sources • one petabyte of raw data • goals: – create accurate, consistent variant calls across all samples – harmonized, cleaned phenotype data – data are not just accessible but usable by researchers from the wider community Key challenges • Logistics: moving, storing and crunching large data-sets • Harmonization: integrating and cleaning data from multiple sources • Analysis: extracting useful information from massive, structured data-sets • Access: making data available and usable for many different audiences Logistics: data management • 100,000 exomes 1 petabyte raw data – with 10 Gbit connection, 1-6 months – may be faster to use truck full of hard drives • data storage is not free: – expect ~$1M/year for 100K exomes • ~10x greater for WGS; less with compression • but community now has extensive experience in handling large sequence data: logistical problems are soluble Logistics: QC and meta-data • sample-tracking: – genetic data: easy ID of duplicates, sample swaps, pedigree and population errors
    [Show full text]
  • Ryan L. Collins
    RYAN LEWIS COLLINS Ph.D. Candidate, Bioinformatics and Integrative Genomics Ph.D. Program, Harvard Medical School 185 Cambridge St., Floor 5 Boston, MA, 02114 NSF Graduate Research Fellow, Talkowski Laboratory, Massachusetts General Hospital (603) 290-2200 Team Leader, Population Genetics & Genome Biology, Broad-SV Group, Broad Institute of MIT and Harvard www.RyanLCollins.com [email protected] § Professional status: third-year Ph.D. § Career objective: to advance knowledge § Scientific interests: structural variation, candidate at Harvard Medical School of the structure-function dynamics in the chromatin, genome topology, sequencing studying human genome structure & human genome, and their implications for technologies, interpretation of genetic function in the lab of Dr. Michael development, disease, population genetics, variation, gene regulation & regulatory Talkowski at Massachusetts General and precision medicine, ideally by leading elements, statistics, predictive modeling, Hospital and The Broad Institute. an independent research group. bioinformatics, and clinical genetics. EDUCATION DEGREES Ph.D. Harvard Medical School, Boston, MA, USA 2016-Present Division of Medical Sciences: Bioinformatics and Integrative Genomics Thesis Title The properties of natural selection on structural variation in the human genome Advisor Michael E. Talkowski, Ph.D. Dissertation Committee Shamil Sunyaev, Ph.D.; Mark Daly, Ph.D.; James Gusella, Ph.D.; Marcin Imielinski, M.D., Ph.D. A.B. Dartmouth College, Hanover, NH, USA 2009-2013 Department
    [Show full text]
  • The Genome Analysis Toolkit: a Mapreduce Framework for Analyzing Next-Generation DNA Sequencing Data
    The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation McKenna, A., M. Hanna, E. Banks, A. Sivachenko, K. Cibulskis, A. Kernytsky, K. Garimella, et al. “The Genome Analysis Toolkit: A MapReduce Framework for Analyzing Next-Generation DNA Sequencing Data.” Genome Research 20, no. 9 (September 1, 2010): 1297–1303. As Published http://dx.doi.org/10.1101/gr.107524.110 Publisher Cold Spring Harbor Laboratory Press Version Final published version Citable link http://hdl.handle.net/1721.1/88421 Terms of Use Creative Commons Attribution-Noncommerical Detailed Terms http://creativecommons.org/licenses/by-nc/3.0/ Downloaded from genome.cshlp.org on June 16, 2014 - Published by Cold Spring Harbor Laboratory Press The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data Aaron McKenna, Matthew Hanna, Eric Banks, et al. Genome Res. 2010 20: 1297-1303 originally published online July 19, 2010 Access the most recent version at doi:10.1101/gr.107524.110 Supplemental http://genome.cshlp.org/content/suppl/2010/07/14/gr.107524.110.DC1.html Material References This article cites 26 articles, 13 of which can be accessed free at: http://genome.cshlp.org/content/20/9/1297.full.html#ref-list-1 Creative This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the Commons first six months after the full-issue publication date (see License http://genome.cshlp.org/site/misc/terms.xhtml).
    [Show full text]
  • Genome-Wide Association Study Reveals First Locus for Anorexia Nervosa and Metabolic Correlations
    HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Am J Psychiatry Manuscript Author . Author Manuscript Author manuscript; available in PMC 2018 September 01. Published in final edited form as: Am J Psychiatry. 2017 September 01; 174(9): 850–858. doi:10.1176/appi.ajp.2017.16121402. Genome-Wide Association Study Reveals First Locus for Anorexia Nervosa and Metabolic Correlations Laramie Duncan, PhD, Zeynep Yilmaz, PhD, Raymond Walters, PhD, Jackie Goldstein, PhD, Verneri Anttila, PhD, Brendan Bulik-Sullivan, PhD, Stephan Ripke, MD, PhD, Eating Disorders Working Group of the Psychiatric Genomics Consortium, Laura Thornton, PhD, Anke Hinney, PhD, Mark Daly, PhD, Patrick Sullivan, MD, FRANZCP, Eleftheria Zeggini, PhD, Gerome Breen, PhD, and Cynthia Bulik, PhD Abstract Objective—To conduct a genome-wide association study (GWAS) of anorexia nervosa and to calculate genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Method—Following uniform quality control and imputation using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, we performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression (LDSC) was used to calculate genome-wide common variant heritability [ , partitioned heritability, and genetic correlations (rg)] between anorexia nervosa and other phenotypes. Results—Results were obtained for 10,641,224 single nucleotide polymorphisms (SNPs) and insertion-deletion variants with minor allele frequency > 1% and imputation quality scores > 0.6. The of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation.
    [Show full text]
  • Studying Genetic Variation II: Computational Techniques
    Studying Genetic Variation II: Computational Techniques Jim Mullikin, PhD Genome Technology Branch NHGRI Some points from the previous two lectures • Genetic maps, markers and linkage analysis by Elaine Ostrander – Genome wide scans for Mendelian inherited disease, microsatellites are still an effective marker to use • Genetic Variation I: Laboratory Techniques by Karen Mohlke – Types of polymorphisms and genotyping methods, focusing primarily on SNP genotyping 1 Overview of Topics • Genome variation origins • Types of polymorphisms • SNP discovery methods • Access to genetic variation data • How to find SNPs in a region of interest • Haplotype Map project Overview of Topics • Genome variation origins • Types of polymorphisms • SNP discovery methods • Access to genetic variation data • How to find SNPs in a region of interest • Haplotype Map project 2 Discovery methods • The primary method for discovering polymorphisms is by sequencing DNA and comparing the sequences. Trace Archive Search query: trace_name='S213P602260RC9.T0' OR trace_name='50766946' 3 Mining SNPs from sequence • EST mining • Clone overlap • The SNP Consortium (TSC) • Targeted resequencing • Haplotype Map Project (HapMap) • Chip based sequencing arrays Expressed Sequence Tag Mining • These sequences are primarily associated with coding regions of genes. • By clustering these sequences, selected differences are identified as SNPs. • There are over 100,000 SNPs in dbSNP from a variety of species detected from clustered ESTs. • The following example is from the CGAP SNP project (see refs). 4 Clone Overlap • The human genome was sequenced from BAC clones (containing about 150kb of sequence each). • These overlapped to various levels, and within the overlap regions, high quality base differences indicated the position and alleles of SNPs.
    [Show full text]
  • Curriculum Vitae: Ryan L. Collins
    RYAN LEWIS COLLINS Ph.D. Candidate, Bioinformatics and Integrative Genomics Ph.D. Program, Harvard Medical School 185 Cambridge St., Floor 5 Boston, MA, 02114 NSF Graduate Research Fellow, Talkowski Laboratory, Massachusetts General Hospital (603) 290-2200 Team Leader, Population Genetics & Genome Biology, Broad-SV Group, Broad Institute of MIT and Harvard www.RyanLCollins.com [email protected] § Professional status: fourth-year Ph.D. § Career objective: to advance knowledge § Scientific interests: structural variation, candidate at Harvard Medical School of the structure-function dynamics in the chromatin, genome topology, sequencing studying human genome structure & human genome and their implications for technologies, interpretation of genetic function in the lab of Dr. Michael development, disease, population genetics, variation, gene regulation & regulatory Talkowski at Massachusetts General and precision medicine, ideally by leading elements, statistics, predictive modeling, Hospital and The Broad Institute. an independent research group. bioinformatics, and medical genetics. EDUCATION DEGREES Ph.D. Harvard University, Cambridge, MA, USA 2016-Present Division of Medical Sciences: Bioinformatics and Integrative Genomics Thesis Title The properties of natural selection on structural variation in the human genome Advisor Michael E. Talkowski, Ph.D. Dissertation Committee Shamil Sunyaev, Ph.D.; Mark Daly, Ph.D.; James Gusella, Ph.D.; Marcin Imielinski, M.D., Ph.D. A.B. Dartmouth College, Hanover, NH, USA 2009-2013 Department of
    [Show full text]
  • AC NEJM CH16 Release
    Media Contact : Kathryn Morris KMorrisPR 845-635-9828 [email protected] Research Published in New England Journal of Medicine Identifies New Chromosome Abnormality Strongly Associated with Autism Spectrum Disorders -- Autism Consortium Releases First Significant Findings from Scan of 3,000 Children and Families with Autism Spectrum Disorders -- BOSTON – JANUARY 09, 2007 – The Autism Consortium, an innovative research, clinical and family collaboration dedicated to radically accelerating research and enhancing clinical care for autism spectrum disorders (ASDs), reported strong and compelling evidence that a region on chromosome 16 appears to play an important role in susceptibility for ASDs. ASDs are diagnosed in as many as 1 in 150 children under the age of three. Symptoms can range from mild to severe and can include social, cognitive and behavioral deficits. The new findings, published online in advance of an upcoming issue of The New England Journal of Medicine (NEJM), are of particular significance because either a deletion or duplication of this section of chromosome 16 appears to contribute strongly to susceptibility to ASDs. In the majority of cases the deletion was de novo , a newly occurring change in the DNA that the affected individual did not directly inherit from either parent. The authors verified the clinical importance of their findings through independent observations in the Genetics Diagnostics Laboratory at Children’s Hospital Boston, a member of the Autism Consortium, and at deCODE Genetics Inc. in Iceland. The research team was led by Mark J. Daly, PhD, an Autism Consortium member at the Center for Human Genetic Research and the Department of Medicine at Massachusetts General Hospital; he is also a senior associate member of the Broad Institute of the Massachusetts Institute of Technology and Harvard.
    [Show full text]
  • PLINK Gplink Haploview Whole Genome Association Software Tutorial
    PLINK gPLINK Haploview Whole genome association software tutorial Shaun Purcell Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Broad Institute of Harvard & MIT, Cambridge, MA http://pngu.mgh.harvard.edu/purcell/plink/ http://www.broad.mit.edu/mpg/haploview/ PLINK tutorial, December 2006; Shaun Purcell, [email protected] PLINK tutorial, December 2006; Shaun Purcell, [email protected] GUI for many PLINK analyses Data management Summary statistics Population stratification Association analysis IBD-based analysis PLINK tutorial, December 2006; Shaun Purcell, [email protected] Computational efficiency 350 individuals genotyped on 100,000 SNPs Load, filter and analyze ~12 seconds 1 permutation (all SNPs) ~1.6 seconds 5000 individuals genotyped on 500,000 SNPs Load PED file, ~68 minutes generate binary PED file Load and filter binary PED file ~11 minutes Basic association analysis ~5 minutes PLINK tutorial, December 2006; Shaun Purcell, [email protected] gPLINK / PLINK in “remote mode” Secure Shell networking Server, or cluster head node W W W gPLINK & Haploview: PLINK, WGAS data initiating and viewing jobs & computation PLINK tutorial, December 2006; Shaun Purcell, [email protected] AA simulatedsimulated WGASWGAS datasetdataset SummarySummary statisticsstatistics andand qualityquality controlcontrol WholeWhole genomegenome SNP-basedSNP-based associationassociation WholeWhole genomegenome haplotype-basedhaplotype-based associationassociation AssessmentAssessment ofof
    [Show full text]
  • In Ammatory and Infectious Upper Respiratory Diseases Associate With
    Inammatory and infectious upper respiratory diseases associate with 59 genomic loci that link to type 2 inammation genes Elmo Saarentaus University of Helsinki https://orcid.org/0000-0002-8475-7187 Juha Karjalainen The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA Joel Rämö Helsinki Institute of Life Science Tuomo Kiiskinen Institute for Molecular Medicine Finland https://orcid.org/0000-0002-6306-8227 Aki Havulinna Helsinki Institute of Life Science Juha Mehtonen Helsinki Institute of Life Science Heidi Hautakangas Helsinki Institute of Life Science Sanni Ruotsalainen Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki https://orcid.org/0000-0002-1631-4069 Sanna Salmi Helsinki Institute of Life Science Matti Pirinen University of Helsinki https://orcid.org/0000-0002-1664-1350 Mitja Kurki Helsinki Institute of Life Science Samuli Ripatti Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki Mark Daly Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki Tuula Palotie Helsinki Institute of Life Science Antti Mäkitie Helsinki Institute of Life Science Aarno Palotie ( aarno.palotie@mm. ) Helsinki Institute of Life Science Genetics Article Keywords: upper respiratory diseases, autoimmune disease, inammation genes Posted Date: July 12th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-654053/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License 1 Inflammatory and infectious upper respiratory diseases associate with 59 2 genomic loci that link to type 2 inflammation genes 3 Authors: Elmo C. Saarentaus1, Juha Karjalainen1,2,3, Joel T. Rämö1, Tuomo Kiiskinen1,4, Aki S.
    [Show full text]
  • Abstracts 2020
    Abstracts 2020 Abstract book sponsored by Talks Page Session 1 …………………………………………………2 Session 2 …………………………………………………3 Session 3 …………………………………………………6 Session 4 …………………………………………………9 Session 5 ………………………………………………..11 Session 6 ………………………………………………..15 Session 7 ………………………………………………..20 Session 8 ………………………………………………..23 Session 9 ………………………………………………..27 Session 10 ………………………………………………..33 Session 11 ………………………………………………..39 Session 12 ………………………………………………..43 Session 13 ………………………………………………..49 Session 14 ………………………………………………..53 Session 15 ………………………………………………..54 Session 16 ………………………………………………..58 Session 17 ………………………………………………..61 Session 18 ………………………………………………..64 Session 19 ………………………………………………..70 Session 20 ………………………………………………..76 Session 21 ……………………………………………… 80 Session 22 ………………………………………………..85 Session 23 ………………………………………………..88 Session 24 ……………………………………………… 91 Session 25 ………………………………………………. 94 Poster Presentations……………………………97-279 1 316 Quantitative Genetics Isn’t Dead Yet Professor Peter M. Visscher1 1Institute for Molecular Bioscience, University of Queensland, ST LUCIA, Australia Session 1, November 3, 2020, 7:00 AM - 8:30 AM Biography: Peter Visscher FRS is a quantitative geneticist with research interests focussed on a better understanding of genetic variation for complex traits in human populations, including quantitative traits and disease, and on systems genomics. The first half of his research career to date was predominantly in livestocK genetics (animal breeding is applied quantitative genetics), whereas the last 15 years he has contributed to methods,
    [Show full text]